Adaptive Fuzzy Robust Control of a Bionic Mechanical Leg With a High Gain Observer

In this paper, an observer-based adaptive fuzzy robust controller is proposed for trajectory tracking control of a bionic mechanical leg (BML) with unmeasured system states, dynamic uncertainties and external disturbances. A high gain observer (HGO) is constructed to estimate the unavailable joint velocities using the joint position feedback signals, while an adaptive fuzzy logic system (AFLS) is employed to address the lumped uncertainties. The nonlinear robust controller is then synthesized via backstepping method to improve the position tracking performance. The stability of the closed loop system is mathematically demonstrated via the Lyapunov's stability theory. It is proven that under the proposed controller all the closed-loop signals are bounded and the trajectory tracking errors converge to a small neighborhood of the origin with appropriate design parameters. The effectiveness of the proposed control scheme is illustrated by simulation studies.